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MDLPCC: Misalignment-aware dynamic LiDAR point cloud compression

delete2025-05-24
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OA
AI
A
Ao Luo
L
Linxin Song
K
Keisuke Nonaka
J
Jinming Liu
K
Kyohei Unno
K
Kohei Matsuzaki
J
Jiro Katto
DOI:10.1016/j.jvcir.2025.104481delete
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Abstract

Abstract

En 中文
• MDLPCC has a global transformation method which solves macroscopic misalignment. • MDLPCC uses sibling spatial information which alleviates microscopic misalignment. • Experiments show MDLPCC attains SOTA RD performance compared with existing methods.
Keywords:
Point cloud compression
Point cloud registration
Motion estimation

Journal

Journal of Visual Communication and Image Representation cover
Journal of Visual Communication and Image Representation
IF:
3.1
Papers:
548
Citations:
5.6K

Organization

No organization information available
Cited Papers

Cited Papers

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PnPNet: End-to-End Perception and Prediction With Tracking in the Loop
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errMing Liang; Bin Yang; Wenyuan Zeng; Yun Chen; Rui Hu; Sergio Casas; Raquel Urtasun
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Inter-Frame Compression for Dynamic Point Cloud Geometry Coding
err2024-01-01
err5
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errAkhtar, Anique; Li, Zhu; van der Auwera, Geert
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